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Compartmental Models of the COVID-19 Pandemic: A Systematic Literature Review

Yıl 2023, , 254 - 267, 31.12.2023
https://doi.org/10.55117/bufbd.1395736

Öz

As COVID-19 rapidly spread all around the world, different methods have been proposed to explore the dynamics of the pandemic, understand the transmission mechanism, and assess the preventive measures. Mathematical models are frequently used worldwide to predict various parameters and develop effective policies for disease control. Compartmental models are the most popular mathematical models in epidemiology. These models divide the population into distinct groups (compartments) based on their status and describe the movement of an individual from one compartment to another. Various compartmental models and their variations have been developed to model the pandemic dynamics and measure the efficiency and necessity of different initiatives such as lockdowns, face masks, and vaccination. This paper provides a systematic literature review on different compartmental models proposed to model the COVID-19 pandemic. These models are discussed in detail based on the compartmental structure in the model, aim of the model, variables, and methodological approaches.

Kaynakça

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COVID-19 Pandemisinin Kompartman Modelleri: Sistematik Bir Literatür Taraması

Yıl 2023, , 254 - 267, 31.12.2023
https://doi.org/10.55117/bufbd.1395736

Öz

COVID-19 hızla tüm dünyada yayılırken, bu pandeminin çeşitli yönleriyle ilgili çok sayıda çalışma yayınlanmıştır. Pandeminin dinamiklerini araştırmak, bulaşma mekanizmasını anlamak ve önleyici tedbirleri değerlendirmek için farklı yöntemler önerilmiştir. Matematiksel modeller, enfeksiyonun seyri için çeşitli parametreleri tahmin etmek ve hastalık kontrolü için etkili politikalar geliştirmek için dünya çapında sıklıkla kullanılmaktadır. Kompartman modelleri epidemiyolojideki en popüler matematiksel modellerdir. Bu modeller, popülasyonu durumlarına göre ayrı gruplara (kompartman) böler ve bir bireyin bir kompartmandan diğerine hareketini tanımlar. Pandeminin dinamiklerini modellemek ve karantina, yüz maskeleri ve aşılama gibi farklı girişimlerin etkinliğini ve gerekliliğini ölçmek için çeşitli kompartman modelleri ve varyasyonları geliştirilmiştir. Bu makale, literatürde COVID-19 pandemisini modellemek için önerilen farklı kompartman modelleri üzerine sistematik bir literatür taraması sunmaktadır. Bu modeller, modeldeki kompartman yapısı, modelin amacı, değişkenler ve metodolojik yaklaşımlar temelinde ayrıntılı olarak ele alınmıştır.

Kaynakça

  • [1] J. Riou, and C. L. Althaus, “Pattern of early human-to-human transmission of Wuhan 2019 novel coronavirus (2019-nCoV), December 2019 to January 2020”, Euro Surveill, 25(4), 2020.
  • [2] World Health Organization Web Page. (2023, January 6). https://covid19.who.int
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  • [4] H. Leite, I.R. Hodgkinson, and T. Gruber, “New development: ‘Healing at a distance’—telemedicine and COVID-19”, Public Money & Management, 40(6), pp. 483–485, 2020.
  • [5] A. Hurajova, D. Kolllarova, and L. Juraj, “Trends in education during the pandemic: modern online technologies as a tool for the sustainability of university education in the field of media and communication studies”, Heliyon, 8(5), pp. 2405-8440, 2022.
  • [6] C. S. M. Currie, J. W. Fowler, K. Kotiadis, T. Monks, B. S. Onggo, D. A. Robertson, and A. A. Tako, “How simulation modelling can help reduce the impact of COVID19”, Journal of Simulation, 14(2), pp. 83-97, 2020.
  • [7] S. Khalilpourazari, and H.H. Doulabi, “Robust modelling and prediction of the COVID-19 pandemic in Canada”, International Journal of Production Research, 2021.
  • [8] M. Liu, R. Thomadsen, and S. Yao, “Forecasting the spread of COVID-19 under different reopening strategies”, Scientific Reports, 10(2036), 2020.
  • [9] S.S. Nadim, I. Ghosh, and J. Chattopadhyay, “Short-term predictions and prevention strategies for COVID-19: A model-based study”, Applied Mathematics and Computation. 404(126251), 2021.
  • [10] F. Brauer, “Compartmental models in epidemiology. In Mathematical epidemiology”, Springer, Berlin, Heidelberg, pp. 19-79, 2008.
  • [11] G. Massonis, J. R. Banga, and A. F. Villaverde, “Structural identifiability and observability of compartmental models of the COVID-19 pandemic” Annual reviews in control, 51, pp. 441–459, 2021. [12] D. Prodanov, “Comments on some analytical and numerical aspects of the SIR model”, Applied Mathematical Modelling, 95, 2021.
  • [13] T. Verma, and A.K. Gupta, “Network synchronization, stability and rhythmic processes in a diffusive mean-field coupled SEIR model”, Communications in Nonlinear Science and Numerical Simulation, 10, 2021.
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  • [15] X. X. Liu, S. J. Fong, N. Dey, R. G. Crespo, and E. Herrera-Viedma, “A new SEAIRD pandemic prediction model with clinical and epidemiological data analysis on COVID-19 outbreak”, Applied intelligence, 51(7), pp. 4162–4198, 2021.
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  • [17] C.B.A. Satrio, W. Darmawan, B.U. Nadia, and N. Hanafiah, “Time series analysis and forecasting of coronavirus disease in Indonesia using ARIMA model and PROPHET”, Procedia Computer Science, 179, pp. 524-532, 2021.
  • [18] V. Vig, and A. Kaur, “Time series forecasting and mathematical modeling of COVID-19 pandemic in India: a developing country struggling to cope up”, International Journal of System Assurance Engineering and Management, 13(6), pp. 2920-2933, 2022.
  • [19] H. Bilgil, “New grey forecasting model with its application and computer code”, AIMS Mathematics, 6(2), pp. 1497–1514, 2020.
  • [20] A. Saxena, “Grey forecasting models based on internal optimization for Novel Corona virus (COVID-19)”, Applied Soft Computing, Vol. 111, 107735, 2021.
  • [21] D.N. Vinod, and S.R.S. Prabaharan, “COVID-19-The Role of Artificial Intelligence, Machine Learning, and Deep Learning: A Newfangled”, Archives of Computational Methods in Engineering, 30(4), pp. 2667-2682, 2023.
  • [22] A. Kumar, P.K. Gupta, and A. Srivastava, “A review of modern technologies for tackling COVID-19 pandemic”, Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 14(4), pp. 569-573, 2020.
  • [23] L. Kong, M. Duan, J. Shi, J. Hong, Z. Chang, and Z. Zhang, “Compartmental structures used in modelling COVID-19: a scoping review”, Infectious Diseases of Poverty, 11 (72), 2022.
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Toplam 86 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Endüstri Mühendisliği
Bölüm Derleme
Yazarlar

Deniz Yerinde 0000-0001-8077-6121

Merve Er 0000-0003-3167-2961

Erken Görünüm Tarihi 31 Aralık 2023
Yayımlanma Tarihi 31 Aralık 2023
Gönderilme Tarihi 24 Kasım 2023
Kabul Tarihi 26 Aralık 2023
Yayımlandığı Sayı Yıl 2023

Kaynak Göster

APA Yerinde, D., & Er, M. (2023). Compartmental Models of the COVID-19 Pandemic: A Systematic Literature Review. Bayburt Üniversitesi Fen Bilimleri Dergisi, 6(2), 254-267. https://doi.org/10.55117/bufbd.1395736
AMA Yerinde D, Er M. Compartmental Models of the COVID-19 Pandemic: A Systematic Literature Review. Bayburt Üniversitesi Fen Bilimleri Dergisi. Aralık 2023;6(2):254-267. doi:10.55117/bufbd.1395736
Chicago Yerinde, Deniz, ve Merve Er. “Compartmental Models of the COVID-19 Pandemic: A Systematic Literature Review”. Bayburt Üniversitesi Fen Bilimleri Dergisi 6, sy. 2 (Aralık 2023): 254-67. https://doi.org/10.55117/bufbd.1395736.
EndNote Yerinde D, Er M (01 Aralık 2023) Compartmental Models of the COVID-19 Pandemic: A Systematic Literature Review. Bayburt Üniversitesi Fen Bilimleri Dergisi 6 2 254–267.
IEEE D. Yerinde ve M. Er, “Compartmental Models of the COVID-19 Pandemic: A Systematic Literature Review”, Bayburt Üniversitesi Fen Bilimleri Dergisi, c. 6, sy. 2, ss. 254–267, 2023, doi: 10.55117/bufbd.1395736.
ISNAD Yerinde, Deniz - Er, Merve. “Compartmental Models of the COVID-19 Pandemic: A Systematic Literature Review”. Bayburt Üniversitesi Fen Bilimleri Dergisi 6/2 (Aralık 2023), 254-267. https://doi.org/10.55117/bufbd.1395736.
JAMA Yerinde D, Er M. Compartmental Models of the COVID-19 Pandemic: A Systematic Literature Review. Bayburt Üniversitesi Fen Bilimleri Dergisi. 2023;6:254–267.
MLA Yerinde, Deniz ve Merve Er. “Compartmental Models of the COVID-19 Pandemic: A Systematic Literature Review”. Bayburt Üniversitesi Fen Bilimleri Dergisi, c. 6, sy. 2, 2023, ss. 254-67, doi:10.55117/bufbd.1395736.
Vancouver Yerinde D, Er M. Compartmental Models of the COVID-19 Pandemic: A Systematic Literature Review. Bayburt Üniversitesi Fen Bilimleri Dergisi. 2023;6(2):254-67.

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